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Archie Reflex — Gate-0 Dataset (100,000 Audited Rows)

Archie Reflex is a single-transition controller architecture over structured UI and 3D scene state:

instruction→{EXECUTE(action)∣ABSTAIN(reason)}\text{instruction} \rightarrow \{\text{EXECUTE(action)} \mid \text{ABSTAIN(reason)}\}

This Gate-0 dataset provides 100,000 audited training and evaluation rows divided into 10 deterministic 10,000-row shards covering single-step Action IR with a target-runtime backend label (blender, threejs, bevy, motionvector).

Provenance. Rows are generated by a deterministic Python generator from a synthetic scene schema. Scalar spans are computed mechanically at render time and are exact by construction. The backend field is a target-runtime label assigned at generation; no engine executed these actions. Execution-verified corpora from this project are separate and smaller: gate1-10k (10,000 rows, headless Chromium, Playwright, per-row state predicates) and the Blender R1 corpus (5,004 rows, headless Blender, replayed twice, post-state hash matched). Treat this set as schema-grounded supervision for verb/target/span heads, not as an execution benchmark.

Static audit: 0 span-integrity failures, 0 invariant violations

  • Total Rows: 100,000
  • Shards: 10 (10,000 rows each)
  • Total Size: 34.6 MB (Zstandard Parquet)
  • Span Integrity: 0 failures across 100,000 rows (100.0% exact match on Unicode code-point offsets $[start, end)$)
  • Positive / Negative Balance:
    • Positive Executions: ~60.5% (balanced across all 10 positive verbs)
    • Negative Abstentions: ~39.5% (balanced across entity_hallucination, ambiguous_or_underspecified, out_of_domain_creative_planning)
  • Invariants: 0 violations (every positive action references a valid entity or created primitive; every negative action abstains cleanly).

Schema

Column Type Description
id string Unique record identifier (e.g. blender_000000000042)
row_index int64 Global deterministic index
backend string Target runtime (blender, threejs, bevy, motionvector)
user_delta string Surface-form natural language instruction
execute int32 Whether to execute (1) or abstain (0)
verb string Gold action verb (translate, rotate, scale, etc., or abstain)
target_entity string Target entity identifier (or null for new primitives / abstentions)
axis string Spatial axis if applicable (X, Y, Z)
scalar_value float64 Target float value
scalar_span_start int32 Character start index of argument span
scalar_span_end int32 Character end index of argument span
scalar_text string Exact substring slice from user_delta
scalar_role string argument or distractor
negative_category string Typed failure code if execute == 0
pre_state_json string Complete JSON scene observation
gold_action_json string Complete canonical Action IR
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